If you've ever watched someone—a learner, a parent, a friend—yourself— get stuck in a response pattern that clearly isn't working anymore, but they keep doing it anyway, you've been face to face with the clinical issues at the heart of today's post. In my last two posts, I've been working through the HDML framework—first the levels of relational responding, then the dimensions of complexity and flexibility. Today I'll cover the remaining two dimensions: derivation and coherence. Both deal with what happens as relational responses become more established over time, and both connect directly to the challenges we all navigate around rigidity, rule governance, and psychological flexibility.

My consultation work always begins with some problem—in some way, someone is “stuck” or they wouldn’t be looking for help from me. In early intervention work that is often a learner who isn’t making progress, and one of the first things I consider is whether the response requirements are too complex and need to be broken down, or whether we haven't built enough flexibility into the repertoire. The HDML framework gives us a way to think about this more precisely. In my last post, I described the levels of relational responding. Today I'll focus on two of the four dimensions of relational framing: complexity and flexibility.

As you know, I’ve been working on some new writing for our updated and expanded text on using RFT to promote generative language (which is still very much a work in progress). One area that has emerged in RFT since we published our first handbook is the Hyper-Dimensional Multi-Level (HDML) framework (Barnes-Holmes and Harte, 2022; Barnes-Holmes et al., 2020; Barnes-Holmes et al., 2017). While the HDML framework was originally conceived as a way of capturing and organizing the variables that conceptual and experimental work in RFT has considered, and for orienting basic researchers to avenues for future work, we also find the framework helpful to organize our thinking with respect to planning intervention. Over the next few posts, I’ll describe how this conceptualization can be viewed in the context of language development and intervention in early childhood.

As Hart and Risley (1999) put so beautifully, language develops through cooperative interactions with others: in describing their analyses of thousands upon thousands of interactions between children and caregivers, they note that “long before the children began saying words, it was clear that they had learned the social skills fundamental to interaction” (p. 36). Within cooperative interactions, we are motivated not only by a particular outcome, but also simply by a motivation to collaborate (Tomasello, 2023). That is, the act of collaboration itself is reinforcing: collaboration may be chosen over solo opportunities to achieve a goal, and collaborative activities may be engaged in “just for fun”; if a partner stops collaborating, whether in a social game or an instrumental task, the other is likely to engage in behavior to re-engage them in the activity. Sharing the experience itself is an important source of reinforcement.

As I mentioned in my last post, we’ve been working on a new chapter for our upcoming comprehensive handbook, on creating cooperative contexts for learning. I have been involved in language-based early intervention in one way or another for most of my career. While much of that work has focused on precise, individualized development of VB and/or RFT-based programming to better establish flexible generative language, it has always begun with establishing a context for learning that is fun and engaging. I used to frame this as establishing “instructional control”, in the sense that we cannot provide instruction unless we have a willing learner who is happy to be with us (and you can see that in the flowchart that accompanies the first volume of myUsing RFT to Promote Generative Language handbook series with Ian Stewart and John McElwee).

This term is a great example of how words have different functions for different people based on our learning histories.